Neurosymbolic AI in Cybersecurity: Bridging Pattern Recognition and Symbolic Reasoning

In the face of escalating cyber threats, traditional security measures often fall short, prompting the need for more advanced and interpretable solutions. Neurosymbolic AI, which synergistically combines the pattern recognition capabilities of neural networks with the explicit reasoning of symbolic systems, presents a promising avenue in this realm. This paper offers a comprehensive exploration of Neurosymbolic AI and its potential in enhancing Intrusion Detection Systems (IDS). By integrating data-driven learning with structured reasoning, Neurosymbolic AI promises more robust, adaptive, and transparent cybersecurity solutions. However, challenges such as model interpretability, data requirements, and adaptability in dynamic threat landscapes persist. This paper provides an overview of these challenges, emphasizing the transformative potential of Neurosymbolic AI in fortifying the cybersecurity domain.